HCC: Medium: Collaborative Research: Development of Trust Models and Metrics for Human-Robot Interaction

人们通常认为，使用机器人来帮助人们执行任务会比人或机器人单独操作产生更好的效果。然而，对自动化系统的研究表明，人机系统的性能取决于人对机器的信任程度以及这种信任（或不信任）的合理程度。随着机器人被开发用于帮助人们完成复杂任务，我们不仅要建立人们可以信任的系统，而且要根据系统的能力培养适当程度的信任，这一点至关重要。对机器人没有适当信任的用户可能会误用或滥用机器人的自主能力，或将人置于危险之中。该项目提出开发量化指标来衡量用户对机器人的信任程度，以及实时估计用户信任程度的模型。利用这些信息，机器人将能够相应地调整其交互。在城市搜索和救援以及辅助机器人等安全关键领域，促进适当程度的信任将特别有益，在这些领域，如果用户对机器人的信任不够，无法依赖其自主能力，则用户可能会对自己、机器人或环境造成伤害。这项研究有可能对人机交互领域产生重大影响，因为很少有研究明确地研究了涉及机器人信任的问题。能够建立信任模型并培养适当的信任水平将导致更有效地使用机器人自动化，更安全的交互和更好的任务性能。

It is often assumed that the use of robots to help people execute tasks will result in better performance than if the person or robot were operating alone. However, research in automated systems suggests that the performance of a human-machine system depends on the extent to which the person trusts the machine and the extent to which this trust (or distrust) is justified. As robots are being developed to aid people with complex tasks, it is critical not only that we build systems which people can trust, but that these systems also foster an appropriate level of trust based on the capabilities of the systems. A user who does not have an appropriate level of trust in the robot may misuse or abuse the robot's autonomous capabilities or expose people to danger. This project proposes to develop quantitative metrics to measure a user's trust in a robot as well as a model to estimate the user's level of trust in real time. Using this information, the robot will be able to adjust its interaction accordingly. Promoting appropriate levels of trust will be particularly beneficial in safety-critical domains such as urban search and rescue and assistive robotics, in which users risk harm to themselves, the robot, or the environment if users do not trust the robot enough to rely on its autonomous capabilities. The research has the potential for a large impact on the field of human-robot interaction as few studies have explicitly examined issues involving trust of robots. Being able to model trust and foster appropriate levels of trust will result in more effective use of robotic automation, safer interactions, and better task performance.